Registration of polarimetric images for in vivo skin diagnostics

SIGNIFICANCE: Mueller matrix (MM) polarimetry is a promising tool for the detection of skin cancer. Polarimetric in vivo measurements often suffer from misalignment of the polarimetric images due to motion, which can lead to false results. AIM: We aim to provide an easy-to-implement polarimetric image data registration method to ensure proper image alignment. APPROACH: A feature-based image registration is implemented for an MM polarimeter for phantom and in vivo human skin measurements. RESULTS: We show that the keypoint-based registration of polarimetric images is necessary for in vivo skin polarimetry to ensure reliable results. Further, we deliver an efficient semiautomated method for the registration of polarimetric images. CONCLUSIONS: Image registration for in vivo polarimetry of human skin is required for improved diagnostics and can be efficiently enhanced with a keypoint-based approach

(SEMI)-AUTOMATED ANALYSIS OF MELANOCYTIC LESIONS

Melanoma is a very aggressive form of skin cancer whose incidence has constantly grown in the last 50 years. To increase the survival rate, an early diagnosis followed by a prompt excision is crucial and requires an accurate and periodic analysis of the patient's melanocytic lesions. We have developed an hardware and software solution named Mole Mapper to assist the dermatologists during the diagnostic process. The goal is to increase the accuracy of the diagnosis, accelerating the entire process at the same time. This is achieved through an automated analysis of the dermatoscopic images which computes and highlights the proper information to the dermatologist. In this thesis we present the 3 main algorithms that have been implemented into the Mole Mapper: A robust segmentation of the melanocytic lesion, which is the starting point for any other image processing algorithm and which allows the extraction of useful information about the lesion's shape and size. It outperforms the speed and quality of other state-of-the-art methods, with a precision that meets a Senior Dermatologist's standard and an execution time that allows for real-time video processing; A virtual shaving algorithm, which increases the precision and robustness of the other computer vision algorithms and provides the dermatologist with a hair-free image to be used during the evaluation process. It matches the quality of state-of-the-art methods but requires only a fraction of the computational time, allowing for computation on a mobile device in a time-frame compatible with an interactive GUI; A registration algorithm through which to study the evolution of the lesion over time, highlighting any unexpected anomalies and variations. Since a standard approach to this problem has not yet been proposed, we define the scope and constraints of the problem; we analyze the results and issues of standard registration techniques; and finally, we propose an algorithm with a speed compatible with Mole Mapper's constraints and with an accuracy comparable to the registration performed by a human operator

Optical Coherence Tomography and Its Non-medical Applications

Optical coherence tomography (OCT) is a promising non-invasive non-contact 3D imaging technique that can be used to evaluate and inspect material surfaces, multilayer polymer films, fiber coils, and coatings. OCT can be used for the examination of cultural heritage objects and 3D imaging of microstructures. With subsurface 3D fingerprint imaging capability, OCT could be a valuable tool for enhancing security in biometric applications. OCT can also be used for the evaluation of fastener flushness for improving aerodynamic performance of high-speed aircraft. More and more OCT non-medical applications are emerging. In this book, we present some recent advancements in OCT technology and non-medical applications

Goggle Augmented Imaging and Navigation System for Fluorescence-Guided Surgery

Surgery remains the only curative option for most solid tumors. The standard-of-care usually involves tumor resection and sentinel lymph node biopsy for cancer staging. Surgeons rely on their vision and touch to distinguish healthy from cancer tissue during surgery, often leading to incomplete tumor resection that necessitates repeat surgery. Sentinel lymph node biopsy by conventional radioactive tracking exposes patients and caregivers to ionizing radiation, while blue dye tracking stains the tissue highlighting only superficial lymph nodes. Improper identification of sentinel lymph nodes may misdiagnose the stage of the cancer. Therefore there is a clinical need for accurate intraoperative tumor and sentinel lymph node visualization. Conventional imaging modalities such as x-ray computed tomography, positron emission tomography, magnetic resonance imaging, and ultrasound are excellent for preoperative cancer diagnosis and surgical planning. However, they are not suitable for intraoperative use, due to bulky complicated hardware, high cost, non-real-time imaging, severe restrictions to the surgical workflow and lack of sufficient resolution for tumor boundary assessment. This has propelled interest in fluorescence-guided surgery, due to availability of simple hardware that can achieve real-time, high resolution and sensitive imaging. Near-infrared fluorescence imaging is of particular interest due to low background absorbance by photoactive biomolecules, enabling thick tissue assessment. As a result several near-infrared fluorescence-guided surgery systems have been developed. However, they are limited by bulky hardware, disruptive information display and non-matched field of view to the user. To address these limitations we have developed a compact, light-weight and wearable goggle augmented imaging and navigation system (GAINS). It detects the near-infrared fluorescence from a tumor accumulated contrast agent, along with the normal color view and displays accurately aligned, color-fluorescence images via a head-mounted display worn by the surgeon, in real-time. GAINS is a platform technology and capable of very sensitive fluorescence detection. Image display options include both video see-through and optical see-through head-mounted displays for high-contrast image guidance as well as direct visual access to the surgical bed. Image capture options from large field of view camera as well high magnification handheld microscope, ensures macroscopic as well as microscopic assessment of the tumor bed. Aided by tumor targeted near-infrared contrast agents, GAINS guided complete tumor resection in subcutaneous, metastatic and spontaneous mouse models of cancer with high sensitivity and specificity, in real-time. Using a clinically-approved near-infrared contrast agent, GAINS provided real-time image guidance for accurate visualization of lymph nodes in a porcine model and sentinel lymph nodes in human breast cancer and melanoma patients with high sensitivity. This work has addressed issues that have limited clinical adoption of fluorescence-guided surgery and paved the way for research into developing this approach towards standard-of-care practice that can potentially improve surgical outcomes in cancer

Computer aided diagnosis system using dermatoscopical image

Computer Aided Diagnosis (CAD) systems for melanoma detection aim to mirror the expert dermatologist decision when watching a dermoscopic or clinical image. Computer Vision techniques, which can be based on expert knowledge or not, are used to characterize the lesion image. This information is delivered to a machine learning algorithm, which gives a diagnosis suggestion as an output. This research is included into this field, and addresses the objective of implementing a complete CAD system using ‘state of the art’ descriptors and dermoscopy images as input. Some of them are based on expert knowledge and others are typical in a wide variety of problems. Images are initially transformed into oRGB, a perceptual color space, looking for both enhancing the information that images provide and giving human perception to machine algorithms. Feature selection is also performed to find features that really contribute to discriminate between benign and malignant pigmented skin lesions (PSL). The problem of robust model fitting versus statistically significant system evaluation is critical when working with small datasets, which is indeed the case. This topic is not generally considered in works related to PSLs. Consequently, a method that optimizes the compromise between these two goals is proposed, giving non-overfitted models and statistically significant measures of performance. In this manner, different systems can be compared in a fairer way. A database which enjoys wide international acceptance among dermatologists is used for the experiments.Ingeniería de Sistemas Audiovisuale

The biomedical use of silk: past, present, future

Humans have long appreciated silk for its lustrous appeal and remarkable physical properties, yet as the mysteries of silk are unraveled, it becomes clear that this outstanding biopolymer is more than a high-tech fiber. This progress report provides a critical but detailed insight into the biomedical use of silk. This journey begins with a historical perspective of silk and its uses, including the long-standing desire to reverse engineer silk. Selected silk structure-function relationships are then examined to appreciate past and current silk challenges. From this, biocompatibility and biodegradation are reviewed with a specific focus of silk performance in humans. The current clinical uses of silk (e.g., sutures, surgical meshes, and fabrics) are discussed, as well as clinical trials (e.g., wound healing, tissue engineering) and emerging biomedical applications of silk across selected formats, such as silk solution, films, scaffolds, electrospun materials, hydrogels, and particles. The journey finishes with a look at the roadmap of next-generation recombinant silks, especially the development pipeline of this new industry for clinical use